Title: Innovation Begins at Home

Abstract:
Prof Andy Stanford-Clark, Chief Technologist for Smarter Energy at IBM UK, will discuss the journey from Smart Metering to a future Smart Grid, incorporating the challenges of microgeneration, electric vehicles, intermittent generation, and demand-side management. Focusing specifically on energy saving in the home, Andy will talk about his own home automation system, and aspects of consumer behaviour change linked with that technology. The talk will also give details of a community energy-saving project, and the Isle of Wight EcoIsland project.

Bio:
Professor Andy Stanford-Clark is the Chief Technologist for IBM’s consulting business in Energy and Utilities for the UK and Ireland. He is an IBM Distinguished Engineer, and “Master Inventor” with more than 40 patents. Andy is based at IBM’s Hursley Park laboratories in the UK, and specialises in remote telemetry, energy monitoring and management, Smart Metering and Smart Grid technologies. He has a particular interest in home energy monitoring, home automation, demand-side management, and driving consumer behaviour change. Andy has a BSc in Computing and Mathematics, and a PhD in Computer Science. He is a visiting professor at the University of Newcastle and a Fellow of the British Computer Society.

 Abstract
Obesity, poor diet and lifestyle and the associated health care costs are set to cripple the governmental budgets of most Western countries over the coming decades. The facts of the equation are simple. Energy intake must exceed energy output for weight loss, and living within a healthy weight range has a host of benefits. Most communities understand and acknowledge the facts, but despite their understanding continue to live lifestyles that endanger them in the long term. In this talk Jill Freyne will walk us through two case studies for online and mobile dietary interventions and examine the power and weaknesses of the technology in the fight to engage and sustain individuals in lifestyle change.

Abstract: The study of the interdependence of human movement and social ties of individuals is one of the most interesting research areas in computational social science. Previous studies have shown that human movement is predictable to a certain extent at different geographic scales. One of the open problems is how to improve the prediction exploiting additional available information. In particular, one of the key questions is how to characterise and exploit the correlation between movements of friends and acquaintances to increase the accuracy of the forecasting algorithms. Continue reading

This seminar is suitable for CS3053-RPIC

Abstract
Social network sites (SNSs) such as Facebook and Twitter are used by hundreds of millions of people daily. As such they represent an attractive source of data for research. Many researchers have crawled these SNSs to collect data for projects involving psychology, sociology, health, and of course computer science. But there are many risks to naively crawling an SNS, ranging from data protection and privacy concerns to the reliability of the collected data.

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